{"id":"W4408087141","doi":"10.1007/978-3-031-80676-6_20","title":"Development of LiMCA (Liquid Metal Cleanliness Analyzer) Sensor: A Comprehensive Review","year":2025,"lang":"en","type":"review","venue":"The minerals, metals & materials series","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Spectrum analyzer; Materials science; Engineering; Electrical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0003632977,0.001370788,0.006319114,0.0003017621,0.0001321007,0.00007151396,0.00125791,0.0005984635,0.0001773004],"category_scores_gemma":[0.0002188154,0.0009279758,0.000712253,0.0009836713,0.0003601105,0.0002315845,0.0006049377,0.0004814044,0.00008757103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001597324,"about_ca_system_score_gemma":0.00009764549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007428,"about_ca_topic_score_gemma":0.00001205026,"domain_scores_codex":[0.9948374,0.0003041028,0.002936796,0.0006914634,0.0005067014,0.0007235265],"domain_scores_gemma":[0.9969556,0.0003616762,0.000891066,0.00140662,0.0002997595,0.00008522087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005826341,0.0000759429,1.992779e-8,0.4762989,0.003218607,0.00003387703,0.00007999181,0.0001071029,0.4048592,0.0003102558,0.00505261,0.1099052],"study_design_scores_gemma":[0.00008973954,0.00002612683,8.328364e-8,0.02666957,0.001844558,0.00005202844,0.00005221811,6.521472e-7,0.1259641,0.00005375959,0.8444899,0.0007572371],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001133734,0.9937255,0.00006159737,0.00004178656,0.00171411,0.001658812,0.0005301259,0.0009394698,0.0001948484],"genre_scores_gemma":[0.00005513839,0.9909648,0.006519628,0.0000646769,0.0003259259,0.0005769522,0.0005008892,0.0001789458,0.0008130406],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8394373,"threshold_uncertainty_score":0.9999043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03806965584681966,"score_gpt":0.2983216468621433,"score_spread":0.2602519910153236,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}